A talk I'll be giving at the AMNH
Here’s a talk I’ll be giving about the meteR package at the AMNH:
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29 September 2017
Maximum Entropy
Maximum Entropy
Maximum Entropy
Maximum Entropy
Maximum Entropy
Maximum Entropy
Maximum Entropy and Macroecology
The core of METE
Ecosystem structure function (ESF) Species abundance and metabolic rate distributions follow
Spatial structure function (SSF) Spatial abundance distribution and species area relationship follow
Why theory?
Why theory?
Why theory?
Why theory?
Why theory?
meteR
meteR
install.packages('meteR') # we're live on CRAN!
devtools::install_github('cmerow/meteR') # dev version
library(meteR)
meteR: Data + Core
data(arth) head(arth, n = 3)
## spp count mass ## 1 blacchel 1 4.7480 ## 2 mecyocul 1 1.6490 ## 3 eurynsp1 1 0.2584
meteR: Data + Core
data(arth) head(arth, n = 3)
## spp count mass ## 1 blacchel 1 4.7480 ## 2 mecyocul 1 1.6490 ## 3 eurynsp1 1 0.2584
arthESF <- meteESF(spp = arth$spp, abund = arth$count,
power = arth$mass^0.75)
arthESF # this is the print method
## METE object with state variables: ## S0 N0 E0 ## 76.00 547.00 15868.26 ## ## with Lagrange multipliers: ## la1 la2 ## 0.037929267 0.004960427
meteR: Data + Core
length(unique(arth$spp))
## [1] 76
sum(arth$count)
## [1] 547
sum(arth$mass^0.75 / min(arth$mass^0.75))
## [1] 15868.26
meteR: Data + Core
length(unique(arth$spp))
## [1] 76
sum(arth$count)
## [1] 547
sum(arth$mass^0.75 / min(arth$mass^0.75))
## [1] 15868.26
arthESF_stateVar <- meteESF(S0 = 76, N0 = 547, E0 = 15868.26)
meteR: Data + Core
data(anbo) head(anbo, n = 3)
## row column spp count ## 1 3 3 cabr 3 ## 2 3 3 caspi1 20 ## 3 3 3 crcr 3
meteR: Data + Core
data(anbo) head(anbo, n = 3)
## row column spp count ## 1 3 3 cabr 3 ## 2 3 3 caspi1 20 ## 3 3 3 crcr 3
anboSSF <- meteSSF(spp = anbo$spp, sppID = 'gnwe',
abund = anbo$count, row = anbo$row,
col = anbo$column, A = 1, A0 = 16)
anboSSF
## METE object with state variables: ## n0 A A0 ## 41 1 16 ## ## with Lagrange multipliers: ## [1] 0.3294792
meteR: Prediction + Analysis
arthSAD <- sad(arthESF)
meteR: Prediction + Analysis
arthSAD <- sad(arthESF) plot(arthSAD, ptype = 'rad')
meteR: Prediction + Analysis
arthSAD <- sad(arthESF) plot(arthSAD, ptype = 'rad')
logLik(arthSAD)
## 'log Lik.' -201.8189 (df=2)
meteR: Prediction + Analysis
anboSAR <- meteSAR(spp = anbo$spp, abund = anbo$count,
row = anbo$row, col = anbo$col,
Amin = 1, A0 = 16)
plot(anboSAR)
meteR: Prediction + Analysis
anboSAR <- meteSAR(spp = anbo$spp, abund = anbo$count,
row = anbo$row, col = anbo$col,
Amin = 1, A0 = 16)
plot(anboSAR)
mse(anboSAR)
## [1] 29.79903
The Future
- pika package to integrate quantitative macroecology
- standardized goodness of fit
- more than just SAD, SAR, metabolism
- will be on CRAN and module in Wallace
- meteR (and/or pika) to facilitate self-publishing of data and analyses
Thanks!
ajrominger.github.io
Andy Rominger